Is winter coming? The rise and fall of Artificial Intelligence

There is no doubt in my mind that Artificial Intelligence (or AI as it is more commonly referred to) will revolutionise both our work and home lives. Technologies like neural networks and machine learning have been used for many years for a variety of use cases. But how will these technologies develop, which are the most attractive applications and how fast will these market opportunities will grow?

I was at a Cambridge Wireless event recently, exploring the topic of AI. A presenter from Amazon put this picture up (see below) and asked ‘how many people thought that the office of the future would look like this?’. Less than 5 people in an audience of about 300 thought it would; for starters, why would a robot be using a physical keyboard?, transferring data wirelessly would be far more efficient!

AI’s had a few ‘summers’ and ‘winters’ over the decades, as Monty Barlow at the Cambridge Wireless event shows in the diagram below. Approximate measures like buzz are useful, but I’m more interested in how this technology is going to be commercialised (who’s going to buy what, from whom, for how much and in what volume).

It is possible to forecast the changing competitive landscape using a theory called Diffusion of Innovation. This shows how new technologies are adopted over time; Everett Rogers discovered that groups of consumers (or businesses) tend to adopt new products in a distinct pattern (see below). Each group has different attitudes to new products, so the market landscape changes as adoption progresses through each group.

This is a great tool for forecasters – it means you can predict how fast new products will be taken up, how consumer behaviour will change over time and allows you to hypothesise competitor strategies. With AI, each technology in the market will therefore be at a different point on this curve, which tells us how it is going to behave. For example, voice assistants on smartphones have already moved into the early majority phase of the market, certainly in terms of availability (31% of the world’s population now own a smartphone according to Statista). Plus, Google’s voice recognition accuracy is now 95% and as this improves over time, this will increase consumer use of voice based services.

Diffusion of Innovation gives you a great basis to predict the shape of each technology’s progress. But how fast will it happen? That will be determined by what the key drivers (and barriers to entry) are for each technology. Industry conferences like the Cambridge Wireless one I attended are a good way to stay up to date and hear what the experts think – the picture below shows me talking to Ofcom Group Director and Board Member, Steve Unger.

Despite the technological advances made, the success of AI will be hugely driven by trust! So, in order to hypothesise how the market will develop, the zeitgeist around ‘AI’ needs to be broken down into its specific technologies. AI isn’t robots in our homes (at least not yet); trust will be built up gradually, moving from voice assistants and augmented reality services offered on our smartphones to more sophisticated interactions with AI in the future.

About the author

Jonathan Davenport is Head of Market Analysis and has particular experience of using market and competitor analysis to support strategy development. He works for Milner Strategic Marketing, a business consultancy that helps companies grow their value by delivering a range of services from strategic management consultancy through to specific marketing programmes.